Adaptive illumination for a time-of-flight camera on a vehicle

ABSTRACT

Disclosed are devices, systems and methods for capturing an image. In one aspect an electronic camera apparatus includes an image sensor with a plurality of pixel regions. The apparatus further includes an exposure controller. The exposure controller determines, for each of the plurality of pixel regions, a corresponding exposure duration and a corresponding exposure start time. Each pixel region begins to integrate incident light starting at the corresponding exposure start time and continues to integrate light for the corresponding exposure duration. In some example embodiments, at least two of the corresponding exposure durations or at least two of the corresponding exposure start times are different in the image.

TECHNICAL FIELD

This document relates to image capture and processing.

BACKGROUND

A vehicle can be autonomously controlled to navigate along a path to adestination. Autonomous vehicle control uses sensors to sense theposition and movement of the vehicle, and based on data from thesensors, navigates the vehicle in the presence of stationary and movingobjects. Autonomous vehicle navigation can have important applicationsin the transportation of people, goods and services. One aspect ofautonomous vehicle control, which ensures the safety of the vehicle andits passengers, as well as people and property in the vicinity of thevehicle, is analysis of images generated by image sensors on thevehicle. The images may be analyzed to determine fixed and movingobstacles in the vehicle's path, or in the vicinity of the vehicle.Improved image capture and analysis are needed to improve autonomousvehicle navigation and control.

SUMMARY

Disclosed are devices, systems and methods for processing an image. Inone aspect, an electronic camera apparatus includes an image sensor witha plurality of pixel regions. The apparatus further includes an exposurecontroller. The exposure controller determines, for each of theplurality of pixel regions in an image, a corresponding exposureduration and a corresponding exposure start time. Each pixel regionbegins to integrate incident light starting at the correspondingexposure start time and continues to integrate light for thecorresponding exposure duration. In some example embodiments, at leasttwo of the corresponding exposure durations or at least two of thecorresponding exposure start times are different in the image.

The following features may be included in any combination. The apparatusfurther includes a plurality of gating circuits, one gating circuit foreach of the plurality of pixel regions, wherein each gating circuitbegins exposure of one of the plurality of pixel regions at thecorresponding exposure start time and continues the exposure for thecorresponding exposure duration. Multiple pixel regions correspond to aportion of the image, wherein the portion of the image is of an objectat a distance from the image sensor, and wherein each of the multiplepixel regions have the same exposure start time. The image isrepresentative of a plurality of objects at different distances from theimage sensor, wherein each object corresponds to a different portion ofthe image, and wherein each portion of the image is associated withdifferent pixel regions each with a different corresponding exposurestart time associated with one of the different distances. A lightintensity at each of the plurality of pixel regions determines thecorresponding exposure duration. The distance is determined by one ormore sensors including a LiDAR sensor, a RADAR sensor, or an ultrasonicsensor. The one or more sensors determine positions of moving objectswithin a field of view of the camera. The distance is determined from ahigh-definition map, wherein the high-definition map includes globalpositioning system coordinates for road lanes and objects within a fieldof view of the camera. The high-definition map is updated over time asthe camera moves or as moving objects change location. Thehigh-definition map is updated by predicting the location of the camerausing velocity information about the camera from global positioningsystem data. The high-definition map is updated by predicting thelocation of one of the moving objects using velocity information aboutthe moving object determined at least in part from two or moredetermined positions of the moving object.

In another aspect, a method of generating an image on an electroniccamera is disclosed. The method includes receiving, from one or moredistance sensors, distances between an image sensor and objects imagedby the image sensor, and associating one or more pixel regions of theimage sensor with each of the objects. The method further includesdetermining, from the received distances and the associations of the oneor more pixel regions with the objects, a corresponding exposure starttime for each of the pixel regions to begin exposure to incoming light,and determining, for each pixel region, a corresponding exposureduration, wherein each pixel region continues to be exposed to incominglight starting from the exposure start time and continuing for thecorresponding exposure duration. At least two of the correspondingexposure durations or at least two of the corresponding exposure starttimes are different in the image.

In another aspect, the above-described method is embodied in the form ofexecutable code stored in a computer-readable program medium.

In yet another aspect, a device that is configured or operable toperform the above-described method is disclosed. The device may includea processor that is programmed to implement the method.

The above and other aspects and features of the disclosed technology aredescribed in greater detail in the drawings, the description and theclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example block diagram of a camera system, inaccordance with some example embodiments;

FIG. 2 depicts an illustrative example showing a range of times forelectronic shutters for various pixel regions, in accordance with someexample embodiments;

FIG. 3 depicts a process, in accordance with some example embodiments;and

FIG. 4 depicts an example of an apparatus that can be used to implementsome of the techniques described in the present document, in accordancewith some example embodiments.

DETAILED DESCRIPTION

Visual perception in self-driving or autonomous vehicles requireshigh-reliability cameras in various environments such as environmentsthat are backlit, have low lighting, and so on. Because of imbalancedlight distribution or an insufficient amount of light, the setting of aglobal shutter speed for the entire image sensor that is imaging a scenemay not be feasible. Consistent with the disclosed subject matter is atime-of-flight (ToF) camera such as a Complementary Metal OxideSemiconductor (CMOS)/Charge-Coupled Device (CCD) camera where theexposure to light of individual pixels, or regions of pixels, can becontrolled to achieve different exposures for the different pixels orregions of the image sensor. Different areas in the resulting image maybe generated with different exposure start times and/or exposuredurations. The different exposure start times may be determined in partfrom different distances between the image sensor and the objects in theimage determined from a pre-built high-definition (HD) map or distancesensors such as LiDAR, RADAR, or ultrasonic distance sensors. In someexample embodiments, a light source such as a flash is initiated. Fromthe known location of the flash and the distances between the flash andthe various objects, arrival times at the image sensor for the lightfrom the objects can be determined. Other sensors may determine thelight intensity received from the different objects. From theintensities of the light from the various objects, the amount of timethe electronic shutter should be open for each pixel region can bedetermined.

The techniques described in this patent document provide shutter forindividual pixels or regions of pixels. The electronic shutter controlincorporates information from a high-definition map and/or distancesensors to provide better camera perception in poor lighting conditionsthereby improving camera performance in autonomous driving applications.

FIG. 1 depicts an example block diagram of a camera system 100, inaccordance with some example embodiments. Real-world scene 110 is anexample view from a camera on an autonomous vehicle looking forward,rearward, or to a side. Image sensor 120 captures an image of the scene110. Pixel region controller 130 controls the exposures of regions ofthe image sensor 120. Exposure control module 140 determines theexposure start times and the exposure durations for the various regionsof image sensor 120. To determine the exposure start times, exposurecontrol module 140 may receive distance information related to theobjects in scene 110 from one or more distance sensors such as RADARsensor 154, LiDAR sensor 152, ultrasonic sensor 156, and/orhigh-definition map 150. To determine the exposure durations, exposurecontrol module 140 determines the brightness of the various regions onthe image sensor 120.

In the example of scene 110, objects are included such as tree 114 andblock 112. Tree 114 is closer to image sensor 120 than is box 112. Otherobjects may be in scene 110 (not shown) such as roads, buildings, othervehicles, road signs, bicycles, pedestrians, and the like. Some objectsmay be at the same distance form image sensor 120 and other objects maybe at different distances. Some objects may be more brightly illuminatedthan other objects due to their proximity to a light source, proximityto the image sensor, and/or the reflectivity of the object. Generallycloser and/or more reflective objects appear brighter at the imagesensor and farther and/or less reflective objects appear less bright atthe image sensor.

Image sensor 120 captures an image of the scene 110 including box 112and tree 114 as well as other objects which are at different distancesfrom image sensor 120. Image sensor 120 may be a two-dimensional arrayof pixels where each pixel generates an electrical signal related to thelight intensity impinging on the pixel. When combined together, theelectrical signals corresponding to the individual pixels produce anelectrical representation of the image of scene 110. Image sensor 120may include 1,000,000 pixels or any other number of pixels. Although notshown, optical components such as lenses, apertures, and/or mechanicalshutters may be included in the camera which includes image sensor 120.Image sensor 120 may provide for applying an electronic shutter toindividual pixels or regions of pixels. An electronic shutter is anenabling signal, or a gate, that enables a corresponding pixel or pixelregion to capture incident light when the electronic shutter is open (orthe enabling signal or gate is active) and to not capture incident lightwhen the electronic shutter is closed (or the enabling signal or gate isinactive). Shown at 120 is a two-dimensional array of pixel regionsincluding pixel regions 122, 124, 126, 128, and others. Image sensor 120may be a charge-coupled device or any other type of image sensor that iselectronically gated or shuttered.

Pixel region controller 130 controls the exposure of the pixel regions(or individual pixels) of the image sensor 120. Shown in FIG. 1 is pixelregion controller 132 which controls the exposure of pixel region 122,pixel region controller 134 which controls the exposure of pixel region124, pixel region controller 136 which controls the exposure of pixelregion 126, and pixel region controller 138 which controls the exposureof pixel region 128. Controlling the exposure includes control of whenthe pixel region is exposed to incident light such as an exposure starttime control and an exposure duration control. For example, a chargecoupled device integrates charge due to the incident light starting atthe exposure start time and continues to integrate for the exposureduration.

Exposure control module 140 determines the exposure start times for thevarious pixel regions of image sensor 120—a time when the exposurestarts for each pixel region. Exposure control module 140 may receivedistance information related to the objects in scene 110 from one ormore sensors such as RADAR sensor 154, LiDAR sensor 152, ultrasonicsensor 156, and/or high-definition map 150 as further detailed below.For example, exposure control module 140 can determine when after aflash is initiated at the camera system 100 that the electronic shuttershould open for each pixel region based on the known speed of light, theknown distance between the camera sensor 120 and objects imaged at eachpixel region. As an illustrative example, tree 114 may be imaged by oneor more pixel regions such as pixel region 122. After a light flash (notshown in FIG. 1), the electronic shutter for pixel region 122 can remainclosed after the flash until the light from the flash propagates to tree114, is reflected from tree 114, and propagates back to pixel region122. The electronic shutter is controlled to open at the time the lightarrives at pixel region 122.

Exposure control module 140 may receive distance information related toscene 110 from one or more sensors such as RADAR sensor 154, LiDARsensor 152, ultrasonic sensor 156 and/or high-definition map 150. Asillustrative examples, exposure control module 140 may receive fromLiDAR sensor 152 a distance that tree 114 is from image sensor 120;exposure control module 140 may receive from RADAR sensor 154 a distancethat box 112 is from image sensor 120; exposure control module 140 mayreceive from ultrasonic sensor 156 distances that box 112 and tree 114are from image sensor 120. Exposure control module 140 uses the distanceinformation to determine the exposure start times for the pixel regionsof the image sensor 120.

Exposure control module 140 determines an exposure duration for each ofthe various pixel regions—a length of time that the electronic shutterremains open for each pixel region after opening at each correspondingexposure start time. For example, the electronic shutter correspondingto pixel region 126 may open when light propagates from a flash to tree112, is reflected, and propagates back to pixel region 126. In thisexample, the image of box 112 at pixel region 126 may be brighter thatthe image of tree 114 at pixel region 122. Accordingly, the exposureduration for pixel region 126 may be shorter than the exposure durationfor pixel region 122. The brightness may be determined from signallevels of the pixels or pixel regions in a recent previous image. As anillustrative example, when images are taken at 30 frames per second,there are 33 milliseconds between frames and the image seen from anautonomous vehicle changes little in 33 milliseconds. In this case,pixel values in the previous image corresponding to the intensities inthe previous image may be used to determine the exposure duration forthe same pixel region in a later image. For example, in a first image, apixel region may be saturated or otherwise negatively affected due totoo much light exposure which may be determined using image processingof the values from the pixel region. In this example, on the next imageof the same scene, the exposure duration may be reduced to preventsaturation or other negative impacts based on the values in the previousimage. Objects that appear brighter at the image sensor 120 can have ashorter exposure duration. The exposure duration for each pixel regionmay be adjusted on successive images and the exposure duration of eachpixel region may be adjusted independently from the other pixel regions.In this way, different pixel regions may have different exposuredurations to generate an image that includes the correct exposure forall pixel regions.

Exposure control module 140 may receive distance information fromhigh-definition map 150 which may include a map of known objects in thevicinity of a GPS location provided to the high-definition map 150. Thehigh-definition map 150 may contain detailed information about roads,lanes on the roads, traffic lights, stop signs, buildings, and so on.Using GPS information locating the autonomous vehicle and camera system,the vehicle can be placed in the high-definition map 150. Accordingly,the objects stored in the map at the location of the vehicle can belocated relative to the vehicle. Distances to the objects can bedetermined from the map and the vehicles location. The vehicle'slocation on the map can be updated as the vehicle moves. In someembodiments, the vehicle's location may be advanced to a later time onthe map using a location, velocity, and acceleration information at thelocation at a starting time. In this way, the location of the vehiclemay be determined less frequently and the accuracy of the vehiclelocation between successive location updates can be improved.

FIG. 2 depicts an illustrative example of a diagram 200 showing a rangeof times for the electronic shutters for various pixel regions, inaccordance with some example embodiments. On the horizontal axis istime, and on the vertical axis is a representation of whether anelectronic shutter corresponding to a pixel region is open at 202thereby capturing an image, or closed at 204 thereby not capturing animage. In FIG. 2, time t₀ is the earliest time that the electronicshutter of any of the pixel regions may be opened, and time t₅ is thelatest time that the electronic shutter of any of the pixel regions mayclose. Between times t₁ and t₂ is a representation 220 of an electronicshutter control for one or more pixel regions. The electronic shutteropens at a shutter time t₁ and closes at t₂. Accordingly, in thisexample, t₁ is the exposure start time and the exposure duration ist₂-t₁. Representation 220 corresponds to an object closer to the imagesensor than the object corresponding to representation 230. Betweentimes t₃ and t₄ is a representation 230 of another electronic shuttercontrol for one or more pixel regions. The electronic shutter at 230opens at a shutter start time t₃ and closes at t₄. Accordingly, in thisexample, the exposure duration is t₄-t₃. FIG. 2 depicts two differentelectronic shutter control representations, but any number of differentshutter controls may be used depending on the number of objects andtheir distances from the image sensor. In some example embodiments oneor more pixel regions may have their electronic shutters open more thanonce in an image corresponding to more than one object being imaged bythe same pixel region(s) where the objects are at different distances,or the distance to one object is unknown but one of several values. Theexposure duration t₄-t₃ is greater that the exposure duration t₂-t₁corresponding to the image at the pixel region(s) associated with 230being darker and thus requiring more image capture (or integration) timethan the pixel regions associated with 220.

FIG. 3 depicts a process, in accordance with some example embodiments.At 310, the process includes receiving distances between an image sensorand objects imaged by the image sensor. At 320, the process includesassociating one or more pixel regions of the image sensor with each ofthe objects. At 330, the process includes determining, from the receiveddistances and the associations, an exposure start time for each of thepixel regions to begin exposure to incoming light. At 340, the processincludes determining, for each pixel region, a corresponding exposureduration, wherein each pixel region continues to be exposed to incominglight starting from the exposure start time and continuing for theexposure duration.

At 310, the process includes receiving distances from one or moredistance sensors between an image sensor and objects imaged by the imagesensor. For example, a LiDAR distance sensor may determine a firstdistance between the image sensor and a first object. An ultrasonicdistance sensor may determine a second distance. A RADAR distance sensormay determine a third distance and/or may provide another distancemeasurement to an object whose distance is also determined by anotherdistance sensor. In some example embodiments, the distance may bedetermined to a fixed object associated with the image sensor and thedistance may be corrected by the fixed offset distance.

At 320, the process includes associating one or more pixel regions ofthe image sensor with each of the objects. As an illustrative example,an image sensor may have 100,000 pixel regions, each region including100 pixels for a total of 10,000,000 pixels in the image sensor. In thisexample, a car is imaged on the image sensor. The image of the caroccupies 1,000 pixel regions which are associated with the car object.The car is a distance from the image sensor that is determined by one ormore distance sensors. Other objects may be imaged on the image sensoroccupying a number of different pixel regions dependent on the size ofthe object and its proximity to the image sensor. Associated with theother objects that are various distances from the image sensor that aredetermined by the one or more distance sensors.

At 330, the process includes determining an exposure start time for eachof the pixel regions based on the distances to the objects and theassociations of the one or more pixel regions with the objects. Theexposure start time is an amount of time after an illumination eventsuch as a flash when the light reflected from an object arrives at theimage sensor. Continuing the example above, one or more of the distancesensors may determine that the car is 100 feet from the camera. As such,the time of flight for light generated by a flash at the camera is twicethe one-way time-of-flight. In this example, if the time of flight is 1ns per foot, then 200 ns after the flash, light would arrive at thecamera due to the flash. Accordingly, the exposure start time would beset to 200 ns after the flash for the 1000 pixel regions associated withthe car. Because a car has a complex shape and an orientation relativeto the camera and image sensor, some pixel regions may have differentexposure start times according to the different distances. Pixel regionsassociated with other objects may have different exposure start timesdue to their different distances from the camera.

At 340, the process includes determining a corresponding exposureduration for each pixel region. The exposure duration is the amount oftime after the exposure start time, which starts the capture of animage, that the image capture continues. For example, an exposureduration is the amount of time that a charge-coupled device camerasensor integrates charge due to incident light. Each pixel regioncontinues to be exposed to incoming light starting from itscorresponding exposure start time and continues for its correspondingexposure duration. The exposure duration may be different for pixelregions whose images have different light intensities. For example,pixel regions corresponding to bright areas of an image have shorterexposure durations than pixel regions corresponding to less brightareas. In this way, different pixel regions have different exposuredurations according to the brightness of the associated image areasthereby preventing under exposed image areas and over exposed imageareas. In some example images, at least two of the correspondingexposure durations or at least two of the corresponding exposure starttimes are different in the image.

FIG. 4 depicts an example of an apparatus 400 that can be used toimplement some of the techniques described in the present document. Forexample, the hardware platform 400 may implement the process 300 or mayimplement the various modules described herein. The hardware platform400 may include a processor 402 that can execute code to implement amethod. The hardware platform 400 may include a memory 404 that may beused to store processor-executable code and/or store data. The hardwareplatform 400 may further include a communication interface 406. Forexample, the communication interface 406 may implement one or morecommunication protocols (LTE, Wi-Fi, Bluetooth, and so on).

Implementations of the subject matter and the functional operationsdescribed in this patent document can be implemented in various systems,semiconductor devices, camera devices, digital electronic circuitry, orin computer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Implementations of aspects of thesubject matter described in this specification can be implemented as oneor more computer program products, e.g., one or more modules of computerprogram instructions encoded on a tangible and non-transitory computerreadable medium for execution by, or to control the operation of, dataprocessing apparatus. The computer readable medium can be amachine-readable storage device, a machine-readable storage substrate, amemory device, a composition of matter effecting a machine-readablepropagated signal, or a combination of one or more of them. The term“data processing unit” or “data processing apparatus” encompasses allapparatus, devices, and machines for processing data, including by wayof example a programmable processor, a computer, or multiple processorsor computers. The apparatus can include, in addition to hardware, codethat creates an execution environment for the computer program inquestion, e.g., code that constitutes processor firmware, a protocolstack, a database management system, an operating system, or acombination of one or more of them.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a stand-alone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random-access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Computer readable media suitable for storingcomputer program instructions and data include all forms of nonvolatilememory, media and memory devices, including by way of examplesemiconductor memory devices, e.g., EPROM, EEPROM, and flash memorydevices. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

While this patent document contains many specifics, these should not beconstrued as limitations on the scope of any invention or of what may beclaimed, but rather as descriptions of features that may be specific toparticular embodiments of particular inventions. Certain features thatare described in this patent document in the context of separateembodiments can also be implemented in combination in a singleembodiment. Conversely, various features that are described in thecontext of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Moreover, the separation of various system components in theembodiments described in this patent document should not be understoodas requiring such separation in all embodiments.

Only a few implementations and examples are described and otherimplementations, enhancements and variations can be made based on whatis described and illustrated in this patent document.

What is claimed is:
 1. An electronic camera apparatus, comprising: animage sensor with a plurality of pixel regions; and an exposurecontroller, wherein the exposure controller determines, for each of theplurality of pixel regions in an image, a corresponding exposureduration and a corresponding exposure start time, wherein each pixelregion begins to integrate incident light starting at the correspondingexposure start time and continues to integrate light for thecorresponding exposure duration, and wherein at least two of thecorresponding exposure durations or at least two of the correspondingexposure start times are different for the plurality of pixel regions.2. The apparatus of claim 1, further comprising: a plurality of gatingcircuits, one gating circuit for each of the plurality of pixel regions,wherein each gating circuit begins exposure of one of the plurality ofpixel regions at the corresponding exposure start time and continues theexposure for the corresponding exposure duration.
 3. The apparatus ofclaim 1, wherein multiple pixel regions correspond to a portion of theimage, wherein the portion of the image is of an object at a distancefrom the image sensor, and wherein each of the multiple pixel regionshave the same exposure start time.
 4. The apparatus of claim 1, whereinthe image is representative of a plurality of objects at differentdistances from the image sensor, wherein each object corresponds to adifferent portion of the image, and wherein each portion of the imagehas a different corresponding exposure start time associated with one ofthe different distances.
 5. The apparatus of claim 1, wherein a lightintensity at each of the plurality of pixel regions determines thecorresponding exposure duration.
 6. The apparatus of claim 3, whereinthe distance is determined by one or more sensors including a LiDARsensor, a RADAR sensor, or an ultrasonic sensor.
 7. The apparatus ofclaim 1, wherein the one or more sensors determine positions of movingobjects within a field of view of the camera.
 8. The apparatus of claim3, wherein the distance is determined from a high-definition map,wherein the high-definition map includes global positioning systemcoordinates for road lanes and objects within a field of view of thecamera.
 9. The apparatus of claim 8, wherein the high-definition map isupdated over time as the camera moves or as moving objects changelocation.
 10. The apparatus of claim 8, wherein the high-definition mapis updated by predicting the location of the camera using velocityinformation about the camera from global positioning system data. 11.The apparatus of claim 8, wherein the high-definition map is updated bypredicting the location of one of the moving objects using velocityinformation about the moving object determined at least in part from twoor more determined positions of the moving object.
 12. A method ofgenerating an image on an electronic camera, comprising: receiving, fromone or more distance sensors, distances between an image sensor andobjects imaged by the image sensor; associating one or more pixelregions of the image sensor with each of the objects; determining, fromthe received distances and the associations of the one or more pixelregions with the objects, a corresponding exposure start time for eachof the pixel regions to begin exposure to incoming light; anddetermining, for each pixel region, a corresponding exposure duration,wherein each pixel region continues to be exposed to incoming lightstarting from the exposure start time and continuing for thecorresponding exposure duration, and wherein at least two of thecorresponding exposure durations or at least two of the correspondingexposure start times are different in the image.
 13. The method of claim12, further comprising: gating each pixel region by a gating circuitassociated with the pixel region, wherein each gating circuit beginsexposure of one of the pixel regions at the corresponding exposure starttime and continues the exposure for the corresponding exposure duration.14. The method of claim 12, wherein multiple pixel regions correspond toa portion of the image, wherein the portion of the image is of an objectat a distance from the image sensor, and wherein each of the multiplepixel regions have the same exposure start time.
 15. The method of claim12, wherein the image is representative a plurality of objects atdifferent distances from the image sensor, wherein each objectcorresponds to a different portion of the image, and wherein eachportion of the image has a different corresponding exposure start timeassociated with one of the different distances.
 16. The method of claim12, wherein a light intensity at each of the plurality of pixel regionsdetermines the corresponding exposure duration.
 17. The method of claim14, wherein the distances are determined by one or more distance sensorsincluding a LiDAR sensor, a RADAR sensor, or an ultrasonic sensor. 18.The method of claim 17, wherein the one or more distance sensorsdetermine positions of moving objects within a field of view of thecamera.
 19. The method of claim 14, wherein the distance is determinedfrom a high-definition map, wherein the high-definition map includesglobal positioning system coordinates for road lanes and objects withina field of view of the camera.
 20. The method of claim 19, wherein thehigh-definition map is updated over time as the camera moves or asmoving objects change location.
 21. The method of claim 20, wherein thehigh-definition map is updated by predicting the location of the camerausing velocity information about the camera from global positioningsystem data.
 22. The method of claim 21, wherein the high-definition mapis updated by predicting the location of one of the moving objects usingvelocity information about the moving object determined at least in partfrom two or more determined positions of the moving object.